Dynamic Mapping of Diesel Engine through System identification
Författare
Redaktör
- D. Alberer
- H. Hjalmarsson
- L. del Re
Summary, in English
From a control design point of view, modern diesel engines are dynamic, nonlinear, MIMO systems. This paper presents a method to find low-complexity black-box dynamic models suitable for model predictive control (MPC) of NOx and soot emissions based on on-line emissions measurements. A four-input-five-output representation of the engine is considered, with fuel injection timing, fuel injection duration, exhaust gas recirculation (EGR) and variable geometry turbo (VGT) valve positions as inputs, and indicated mean effective pressure, combustion phasing, peak pressure derivative, NOx emissions, and soot emissions as outputs. Experimental data were collected on a six-cylinder heavy-duty engine at 30 operating points. The identification procedure starts by identifying local linear models at each operating point. To reduce the number of dynamic models necessary to describe the engine dynamics, Wiener models are introduced and a clustering algorithm is proposed. A resulting set of two to five dynamic models is shown to be able to predict all outputs at all operating points with good accuracy.
Avdelning/ar
Publiceringsår
2012
Språk
Engelska
Sidor
223-239
Publikation/Tidskrift/Serie
Identification for Automotive Systems
Volym
LNCIS 418
Fulltext
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Dokumenttyp
Konferensbidrag
Förlag
Springer
Ämne
- Control Engineering
- Other Mechanical Engineering
Nyckelord
- Combustion
- Engine
- Control
- Diesel
- System Identification
Conference name
Workshop on Identification for Automotive Systems
Conference date
2010-07-15
Conference place
Linz, Austria
Status
Published
Projekt
- Competence Centre for Combustion Processes
- Competence Centre for Combustion Processes
- Diesel HCCI in a Multi-Cylinder Engine
Forskningsgrupp
- KCFP
ISBN/ISSN/Övrigt
- ISSN: 0170-8643